MappedTrace: Tracing Pointer Remotely with Compiler-generated Maps

• URL: http://arxiv.org/abs/2501.10668v1
• Date: Sat, 18 Jan 2025 06:22:28 GMT
• Title: MappedTrace: Tracing Pointer Remotely with Compiler-generated Maps
• Authors: Zhiyao Ma, Caihua Li, Lin Zhong,
• Abstract summary: We propose MappedTrace that leverages compiler-generated read-only maps to accurately identify all pointers in any given snapshot of a program's execution state. MappedTrace presents new opportunities to improve memory management techniques like memory leak detection and enables novel use cases such as infinite memory abstraction for resource-constrained environments.
• Score: 4.197499765642787
• License:
• Abstract: Existing precise pointer tracing methods introduce substantial runtime overhead to the program being traced and are applicable only at specific program execution points. We propose MappedTrace that leverages compiler-generated read-only maps to accurately identify all pointers in any given snapshot of a program's execution state. The maps record the locations and types of pointers, allowing the tracer to precisely identify pointers without requiring the traced program to maintain bookkeeping data structures or poll at safe points, thereby reducing runtime overhead. By running the tracer from a different address space or machine, MappedTrace presents new opportunities to improve memory management techniques like memory leak detection and enables novel use cases such as infinite memory abstraction for resource-constrained environments.

Related papers

• Multi-Pass Targeted Dynamic Symbolic Execution [0.0]
  We present a Multi-Pass Targeted Dynamic Execution approach that starts from a target program location and moves backward until it reaches a specified entry point. Our approach achieves on average 4X reduction in the number of paths explored and 2X speedup.
  arXiv  Detail & Related papers  (2024-08-14T20:14:59Z)
• AddressWatcher: Sanitizer-Based Localization of Memory Leak Fixes [6.31619298702529]
  Memory leak bugs are a major problem in C/C++ programs. Several techniques have been proposed to automatically fix memory leaks. Static-based approaches attempt to trace the complete semantics of memory object across all paths. Dynamic approaches can spell out precise semantics of memory object only on a single execution path.
  arXiv  Detail & Related papers  (2024-08-08T21:40:22Z)
• VDebugger: Harnessing Execution Feedback for Debugging Visual Programs [103.61860743476933]
  We introduce V Debugger, a critic-refiner framework trained to localize and debug visual programs by tracking execution step by step. V Debugger identifies and corrects program errors leveraging detailed execution feedback, improving interpretability and accuracy. Evaluations on six datasets demonstrate V Debugger's effectiveness, showing performance improvements of up to 3.2% in downstream task accuracy.
  arXiv  Detail & Related papers  (2024-06-19T11:09:16Z)
• CAMP: Compiler and Allocator-based Heap Memory Protection [23.84729234219481]
  We present CAMP, a new sanitizer for detecting and capturing heap memory corruption. CAMP enables various compiler optimization strategies and thus eliminates redundant and unnecessary check instrumentation. Our evaluation and comparison of CAMP with existing tools, using both real-world applications and SPEC CPU benchmarks, show that it provides even better heap corruption detection capability with lower runtime overhead.
  arXiv  Detail & Related papers  (2024-06-04T19:37:41Z)
• LightDE: A Lightweight Method for Eliminating Dangling Pointers [0.0]
  Use-After-Free (UAF) vulnerabilities pose a serious threat to software security. Existing methods for defending against UAF vulnerabilities by eliminating dangling pointers need to interrupt the program's execution. We propose a novel approach called LightDE to overcome this drawback.
  arXiv  Detail & Related papers  (2024-05-31T08:47:24Z)
• RTracker: Recoverable Tracking via PN Tree Structured Memory [71.05904715104411]
  We propose a recoverable tracking framework, RTracker, that uses a tree-structured memory to dynamically associate a tracker and a detector to enable self-recovery. Specifically, we propose a Positive-Negative Tree-structured memory to chronologically store and maintain positive and negative target samples. Our core idea is to use the support samples of positive and negative target categories to establish a relative distance-based criterion for a reliable assessment of target loss.
  arXiv  Detail & Related papers  (2024-03-28T08:54:40Z)
• Tracking with Human-Intent Reasoning [64.69229729784008]
  This work proposes a new tracking task -- Instruction Tracking. It involves providing implicit tracking instructions that require the trackers to perform tracking automatically in video frames. TrackGPT is capable of performing complex reasoning-based tracking.
  arXiv  Detail & Related papers  (2023-12-29T03:22:18Z)
• Learning Dynamic Compact Memory Embedding for Deformable Visual Object Tracking [82.34356879078955]
  We propose a compact memory embedding to enhance the discrimination of the segmentation-based deformable visual tracking method. Our method outperforms the excellent segmentation-based trackers, i.e., D3S and SiamMask on DAVIS 2017 benchmark.
  arXiv  Detail & Related papers  (2021-11-23T03:07:12Z)
• Video Object Segmentation with Episodic Graph Memory Networks [198.74780033475724]
  A graph memory network is developed to address the novel idea of "learning to update the segmentation model" We exploit an episodic memory network, organized as a fully connected graph, to store frames as nodes and capture cross-frame correlations by edges. The proposed graph memory network yields a neat yet principled framework, which can generalize well both one-shot and zero-shot video object segmentation tasks.
  arXiv  Detail & Related papers  (2020-07-14T13:19:19Z)
• DMV: Visual Object Tracking via Part-level Dense Memory and Voting-based Retrieval [61.366644088881735]
  We propose a novel memory-based tracker via part-level dense memory and voting-based retrieval, called DMV. We also propose a novel voting mechanism for the memory reading to filter out unreliable information in the memory.
  arXiv  Detail & Related papers  (2020-03-20T10:05:30Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.